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Evaluating the Performance of Two Computer Vision Techniques for a Mobile Humanoid Agent Acting at RoboCup KidSized Soccer League Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Non-stationary VFD Evaluation Kit: Dataset and Metrics to Fuel Video-Based Fire Detection Development

verfasst von : Cristiano Rafael Steffens, Ricardo Nagel Rodrigues, Silvia Silva da Costa Botelho

Erschienen in: Robotics

Verlag: Springer International Publishing

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Abstract

Datasets play a major role in the advance of computer vision techniques nowadays. Open, complete and challenging ground truth data, combined with standardized metrics are essential to push the development and allow the proper evaluation of computer vision algorithms. Even though a significant amount of work on VFD (video-based fire detection) systems has been developed, compare different algorithms is a laborious task due to the lack of common evaluation schemes and evaluation datasets. We address both of these issues by presenting a dataset of fire videos along with frame by frame annotations to be used for non-stationary fire detection algorithms training and validation. By the time, this is the largest dataset released on this subject matter. Standard video file formats and open markup languages where used to allow compatibility and convenient integration with the most popular computer vision libraries. The dataset includes hand-held, robot attached and drone attached footages and aims to boost the development of fully autonomous firefighter robots. The presented ground truth and metrics adapt to the majority of the state-of-the-art techniques and provides a reliable and unbiased solution to compare them. The dataset, example source-code and documentation are publicly available under the Creative Commons 3.0 license on GitHub.

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Metadaten
Titel
Non-stationary VFD Evaluation Kit: Dataset and Metrics to Fuel Video-Based Fire Detection Development
verfasst von
Cristiano Rafael Steffens
Ricardo Nagel Rodrigues
Silvia Silva da Costa Botelho
Copyright-Jahr
2016
Buch
Robotics

Print ISBN: 978-3-319-47246-1

Electronic ISBN: 978-3-319-47247-8

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-47247-8_9

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